AI models
Molmo 72B
Training compute
1.3×10²² FLOP
Parameters
72B
Published
Sep 25, 2024
Molmo 72B is an AI model developed by Allen Institute for AI and University of Washington (United States), first published in September 2024. It works in the language, vision and multimodal domain, on tasks such as language modeling/generation, visual question answering and question answering.
Training it took an estimated 1.3×10²² FLOP of compute (estimation method: hardware,operation counting). The model has 72,000,000,000 parameters. Training ran on NVIDIA H100 SXM5 80GB.
Access: Open weights (unrestricted). Its weights are openly available. It is built on top of Qwen2-72B,CLIP (ViT L/14@336px). Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Allen Institute for AI, University of Washington
- Country of organization
- United States
- Domain
- Language, Vision, Multimodal
- Task
- Language modeling/generation, Visual question answering, Question answering
- Training compute
- 1.3×10²² FLOP
- Compute estimation method
- Hardware, Operation counting
- Parameters
- 72,000,000,000
- Training hardware
- NVIDIA H100 SXM5 80GB
- Numerical format
- BF16
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Base model
- Qwen2-72B, CLIP (ViT L/14@336px)
- Epoch confidence
- Confident
More from Allen Institute for AI,University of Washington
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
← All ai models